3044results about "Picking devices" patented technology

A method for generating an agricultural cut-point for an agricultural item includes capturing an image of the agricultural item, generating a depth estimation of the agricultural item, segmenting the image of the agricultural item to generate a segmented image that identifies different segments of the agricultural item, detecting an agricultural feature of the agricultural item based on the image of the agricultural item, generating a two-dimensional cut-point based on the segmented image and the agricultural feature, and generating a three-dimensional cut-point based on the two-dimensional cut-point and the depth estimation of the agricultural item.

The invention provides a double-arm picking robot system and a control method, a robot body is mounted on a moving module through a rotary lifting waist and hip joint, and a storage module is arranged on the moving module; the moving module can drive the robot body and the storage module to move; a right multi-degree-of-freedom mechanical arm and a left multi-degree-of-freedom mechanical arm are arranged on the two sides of the robot body, a right arm tail end picking gripper is arranged at the right end of the right multi-degree-of-freedom mechanical arm, and a left arm tail end picking gripper is arranged at the tail end of the left multi-degree-of-freedom mechanical arm; an image acquisition module is arranged at the top of the robot body, a laser radar module is arranged on the moving module, and the image acquisition module and the laser radar module perform data transmission with the robot control module. Two arms are adopted for cooperative work, the structure of the humanoid mechanical arm is more suitable for the picking scene, and cooperation can be more effectively carried out.

The invention provides a picking mechanical arm operation method and system based on visual feedback. The picking mechanical arm operation method comprises the steps that firstly, a multi-dimensional visual perception set including the shape contour, surface physical characteristic visual representation, connection part space distribution, growth environment dynamic interference and the like of a picked object is obtained; a mechanical arm collaborative decision-making model is constructed based on the multi-dimensional visual perception set, stress distribution characteristics of connection parts are analyzed, and optimal contact area parameters and mechanical arm posture collaborative parameters are determined; according to the parameters, generating a sub-time sequence action instruction set containing action information in the contact stage, the clamping stage and the separation stage; when the mechanical arm is controlled to execute the instruction set, a dynamic visual feedback set of the picking scene is obtained in real time; and finally, input parameters of the collaborative decision model are updated based on feedback, and instruction set parameters are adjusted, so that the mechanical arm completes picking operation on the premise of keeping the integrity of the picked object, and the intelligent level and the picking operation quality of the picking mechanical arm are improved.

The invention relates to the field of intelligent agricultural robots, in particular to a multi-robot collaborative harvesting method and system for woody oil plants based on swarm intelligence, and provides efficient harvesting of the woody oil plants by constructing a distributed sensing network and a semantic enhanced digital twinborn model, and the system adopts a three-layer decision architecture to formulate a harvesting strategy. The working efficiency is improved through self-adaptive task allocation and collaborative harvesting, multiple robots share experience through federated learning, group collaborative learning is achieved, harvesting performance is optimized, the reliability of the system is improved by 85%, single-point fault risks do not exist, the recognition accuracy is improved by 50% through a multi-modal sensing system, and the system is suitable for popularization and application. And an innovative harvesting solution is provided for the field of intelligent agricultural robots.

The invention discloses a control method of a picking robot, and particularly relates to the technical field of intelligent control. According to the method, three-dimensional point cloud data of all fruits in a fruit cluster area are collected in real time, and a spatial connection topological structure of fruit stems is established; establishing a finite element mechanical analysis model based on the spatial connection topological structure of the carpopodium, analyzing a stress transmission path after the picking action acts on the carpopodium, and predicting position deviation of adjacent unpicked fruits; meanwhile, a multi-target path optimization algorithm is adopted to generate an initial path of continuous picking of the picking robot, and then the spatial position of the next fruit picking action is dynamically corrected according to fruit stem stress transmission path data; and abnormal change characteristics of fruit positions and postures are identified according to actual position deviation data of the picking action, so that control parameters and path planning of the next picking action are adjusted in real time. The precision and stability of picking path planning are improved, and the overall efficiency and reliability of picking operation of the robot are improved.

The invention relates to a double-arm intelligent collaborative tea picking method and device based on multi-strategy dynamic scheduling, and belongs to the field of robot automation. The method comprises the following steps: obtaining three-dimensional coordinate information of a target picking point; identifying and positioning potential branch and leaf shields, and generating space data of the shields; the method comprises the following steps: simultaneously projecting a shielding object and a clamping jaw geometric contour under an expected grabbing pose on a plane where a target picking point is located, analyzing the overlapping amount, the proximity and / or the density of the projections of the shielding object and the clamping jaw geometric contour, and generating a standardized shielding evaluation index; comparing the shielding evaluation index with a preset decision threshold, and if the shielding evaluation index is greater than the preset decision threshold, executing a master-slave collaborative picking method based on multi-stage positioning; otherwise, executing the parallel picking method based on dynamic collision-free region division. The problems that a traditional single-arm tea picking robot is low in operation efficiency, high in collision risk and insufficient in intelligent degree in a dense and unstructured tea tree environment are solved.

A factory mushroom picking robot includes a mobile platform, a chassis (100), a lifting device (200), a mushroom stick take-up device (300) and a mushroom picking device (400). The mushroom stick take-up device (300) is configured to take mushroom sticks out of a mushroom rack (4), and the mushroom sticks from different layers are taken through the lifting device (200). The mushroom picking device (400) includes a mechanical arm (402) and an execution end (403). The image data of the mushroom sticks are acquired through three depth cameras. Mushroom targets to be picked are identified through multi-view target matching and are divided in terms of the quality grade, so as to achieve graded picking. A vision-based graded picking method, a mushroom detection and grading method based on multi-view fusion and a non-transitory storage medium of executing corresponding method are further provided.

Described herein are techniques for generating contextually rich plant images. A number of data captures of raw plant data are generated via a sensing unit configured to navigate a growing facility. Metadata is generated and assigned to the raw plant data including at least one of: plant location, timestamp, plant identification, plant strain, facility identification, facility location, facility type, health risk factors, plant conditions, and human observations. Images generated by the sensing unit are analyzed and pixel annotations are generated in the images based on their relation to one or more plant well-being features. Data tags are generated and assigned the data captures based on an analysis of the data captures. The data tags are text phrases linking a particular data capture to a specific threat to plant well-being.

The invention provides a picking robot carrying a multi-modal generation type large model and a picking method. The picking robot comprises a moving device, a control device, a six-axis mechanical arm, a tail end picking executing mechanism, a tail end camera, a side camera, a global camera and sensors. The control device is loaded with a software program, and the software program is loaded with the applied multi-modal generative large model. According to the picking robot carrying the multi-modal generation type large model and the picking method, the RGB image in the real world is directly mapped into the action of the picking robot, so that the picking robot can learn from visual input and simulate and execute a specific action, and when a task of specific picking operation is executed, the picking operation is more accurate, and the picking efficiency is improved. Data acquired from a field environment are imported into the large model in real time, and according to real-time feedback, the action state is adaptively adjusted in the process of executing picking operation according to a planned path, so that the picking accuracy is improved.

The invention relates to the technical field of picking machines, and provides a high-altitude fruit picking device and a picking method.The high-altitude fruit picking device comprises a walking device and a working device; the walking device comprises a walking mechanism, a driving mechanism, a rotating mechanism connected between the walking mechanism and the driving mechanism and a mechanical arm connected with the driving mechanism. The working device comprises an arc-shaped supporting body, an arc-shaped track, a fruit cutting mechanism and a track driving mechanism, the arc-shaped supporting body is connected with the mechanical arm, an arc-shaped moving channel is formed in the arc-shaped supporting body in a penetrating mode, and an arc-shaped receding groove communicating with the arc-shaped moving channel is formed in the inner side wall of the arc-shaped supporting body; the arc-shaped track is assembled in the arc-shaped movable channel in a sliding mode, fruit cutting mechanisms are arranged above the two ends of the arc-shaped supporting body and connected with the arc-shaped track, and the track driving mechanism is connected between the arc-shaped supporting body and the arc-shaped track. The high-altitude fruit picking device has the advantages that the walking distance of the high-altitude fruit picking device in the picking process can be effectively reduced, and the overall picking efficiency is improved.

Methods, devices, and systems, that relate to mechanization of agricultural tasks, including a robotic tool carrier configured to be mounted on a tractor or other type of vehicle and employing imaging and artificial intelligence to perform agricultural tasks, such as pruning, cutting vegetables, or weeding crops.

The invention discloses a tomato stem picking point attitude estimation method, and relates to a computer vision processing technology. The method comprises the following steps: detecting a long-range directional frame target, acquiring a color flow by a depth camera, and detecting position information and shielding conditions of fruits and fruit stems through a directional frame; visual guidance: matching fruit stems based on tomato growth constraint conditions, and visually guiding the mobile platform and the mechanical arm to move in a coupling manner until the fruit stems are observed when the fruit stems are not matched; detecting close-range key points, regulating and controlling a mechanical arm to a close-range observation position, identifying two points of a main stem and three points of a fruit stem through a key point detection model, and extracting point clouds; performing point cloud data processing, removing point cloud noise through point cloud filtering, and performing adaptive compensation on key points with depth anomaly by using a neighborhood mean value; calculating picking poses, and establishing the picking poses of the fruit stem shear points according to the three-dimensional information of the five key points; according to the method, the problem of tomato shielding in a greenhouse complex scene can be effectively solved, and the fruit stem shearing point pose is obtained.

An end effector for a picking robot, and a method of use, the end effector comprising: a body; a shaft slidably coupled to the body and extending along a longitudinal axis between a proximal end and a distal end, the shaft having a vacuum lumen extending therethrough along the longitudinal axis; a suction cup coupled to the distal end of the shaft such that an interior volume of the suction cup is in fluid communication with the vacuum lumen; a vacuum generator connected to the vacuum lumen at the proximal end of the shaft and configured to create suction therethrough; and a linear actuator configured to slide the shaft along the longitudinal axis between an extended position in which the suction cup is relatively farther from the body and a retracted position in which the suction cup is relatively closer to the body.

The invention is applicable to the technical field of agricultural automation equipment, and provides an Ackerman mobile picking robot based on double-vision collaboration, which comprises an Ackerman chassis, a six-degree-of-freedom mechanical arm, a power supply, a power supply and a control system, and further comprises a power supply system, a power supply system, a power supply system and a control system, and the six-degree-of-freedom mechanical arm is provided with a shear type end effector; the global vision module is mounted at the front end of the Ackerman chassis through a two-dimensional holder; the hand-eye vision module is fixedly mounted on the shearing type end effector; and the control unit is integrated in the industrial personal computer. The device has both efficiency and precision, has strong error compensation capability, is reasonable in structure and good in adaptability, and has strong anti-interference capability.

The utility model discloses a fruit picking and subpackaging device which comprises a vehicle body, a support, a guide assembly, a conveying belt, a lower fruit receiving basin, an upper fruit receiving basin and a sorting assembly, the guide assembly comprises a first telescopic cylinder and a second telescopic cylinder, and a picking mechanism and a storage mechanism are arranged at the output end of the second telescopic cylinder. A camera connected with the controller is arranged on the picking mechanism; a stirring mechanism is arranged in the upper fruit receiving basin, the sorting assembly comprises a sorting and receiving hopper assembly, the sorting and receiving hopper assembly comprises a plurality of receiving hoppers, and an electric door mechanism used for controlling fruit discharging is arranged at the discharging end of each receiving hopper; the camera, the picking mechanism and the storage mechanism which are connected with the controller are arranged, so that the picking angle of the fruit picking mechanism is convenient to observe and adjust in real time, and the falling accuracy of picked fruits is improved; a fruit receiving basin, a stirring mechanism, a sorting assembly and an electric door mechanism are arranged to assist the fruits in moving and facilitate rapid classification, packaging and placement.

The invention relates to the technical field of agricultural fruit automatic picking robots, in particular to a finger plate air suction and deflation type approaching triggering variable structure flexible picking manipulator and a control method thereof.The finger plate air suction and deflation type approaching triggering variable structure flexible picking manipulator comprises a support, one end of the support is connected with a mechanical arm through a grabbing driving system, and the other end of the support is connected with a mechanical arm; image acquisition equipment is mounted on the mechanical arm, a variable structure mechanism is mounted in the middle of the support, the support is connected with the finger plate suction and release type grabbing device through the variable structure mechanism, and an approach triggering system is mounted at the other end of the support; the approach triggering system and the image acquisition equipment are in communication connection with the variable structure mechanism and the finger plate suction and release type grabbing device through the grabbing driving system so as to realize self-adaptive automatic picking of fruits; the device has the beneficial effects that finger plate air suction and deflation type grabbing and passive grabbing force control are achieved, proximity type grabbing triggering is achieved, effective grabbing is achieved by changing the grabbing structure according to fruits of different shapes, the fruit picking accuracy is improved, automatic picking is achieved, operation is convenient, and the popularization performance is high.

The utility model provides a tomato picking robot device which comprises a movable chassis, an installation shell is fixedly arranged on the top face of the movable chassis, a visual picking matching component is installed at the left end of the top face of the installation shell, and an auxiliary picking matching mechanism is installed at the right end of the top face of the installation shell. Two multi-direction picking adjusting mechanisms are arranged on one side of the visual picking matching component, each multi-direction picking adjusting mechanism is installed on an installation shell and used for tomato picking operation, and a picking recycling component is installed on the installation shell. According to the tomato picking machine, through the matching arrangement of all the structures, automatic picking operation on tomatoes is facilitated, operation is easy, picking efficiency is high, and popularization is facilitated.

The invention relates to the technical field of soilless culture, and discloses a pepper cultivation and harvesting integrated device which comprises a rail assembly, a bottom plate and a back plate, the lower end of the bottom plate is fixedly connected with two supports, the lower ends of the two supports are jointly and fixedly connected with a transverse plate, and the lower end of the bottom plate is provided with a driving mechanism; the driving mechanism is used for driving the bottom plate to move on the track assembly and can adapt to a line of the track assembly, a support is fixedly connected to the upper end of the bottom plate, a supporting bearing is fixedly connected to the upper end of the support, and a circular plate is fixedly connected to an inner ring of the supporting bearing. According to the pepper cultivation and harvesting integrated device, self-adaptive operation can be conducted according to different growth conditions and environmental nutrition parameters of pepper plants, the automatic picking function can be achieved after the plants are mature, the cultivation procedure of pepper planting can be completed by reducing manual operation, the actual use requirement and the practical requirement are effectively met, and the practicability is high. The production efficiency is improved.

The invention relates to an intelligent climbing coconut tree flexible picking and transporting integrated robot which comprises two open-close type circular rails, a connecting frame, a climbing mechanism, two open-close type clamping arm assemblies, a clamping and picking mechanism and a pruning mechanism, the two open-close type circular rails are distributed up and down in a spaced mode, and the two open-close type circular rails are both automatically opened or closed to form a whole ring; the connecting frame is installed between the non-opening-closing sides of the two sets of opening-closing type circular rails, the climbing mechanism is arranged on the inner side of the connecting frame and used for making contact with a tree trunk and climbing along the tree trunk, and the two sets of opening-closing type clamping arm assemblies are installed on the connecting frame and can be automatically opened or closed to hold the tree trunk. The lower end of the lower opening-closing type clamping arm assembly and the lower end of the connecting frame are jointly provided with a ground walking mechanism, and the clamping picking mechanism and the pruning mechanism are installed on the two sets of opening-closing type annular rails through a set of moving assemblies respectively and can move in the annular direction of the opening-closing type annular rails through the moving assemblies respectively. The robot has the advantages that automatic climbing, picking and transporting walking can be achieved, potential safety hazards are reduced, and picking and transporting efficiency is improved.

The invention relates to the technical field of areca-nut picking, in particular to a flying robot system for areca-nut picking, and adopts the technical scheme that a full-autonomous areca-nut picking robot system is constructed by deeply fusing high-precision multi-source visual perception, intelligent decision planning and compliance control technologies; according to the system, a sensing scheme combining multispectral imaging and structured light three-dimensional measurement is adopted, so that the recognition rate, the positioning precision and the maturity discrimination reliability of areca nuts in a complex illumination and shielding environment are remarkably improved; an extended Kalman filtering and advanced control law-based flight attitude stabilization algorithm effectively inhibits external disturbance and provides necessary platform stability for accurate picking in dynamic flight; the picking executing mechanism with the lightweight design is combined with real-time force feedback control, lossless grabbing of fruits is achieved, and the fruit damage rate is greatly reduced; and due to an intelligent energy management and task planning strategy, the overall energy efficiency of the system is optimized, and the endurance time and the picking quantity of single operation are prolonged.

The invention relates to a fruit and vegetable picking robot system based on data enhancement and identification precision optimization, and belongs to the field of robots. The system is composed of a visual identification module, a mechanical arm module, a control module and a moving module, and fruits and vegetables are identified and positioned in real time by adopting a YOLOv5 target detection algorithm. The visual module collects images through a monocular camera, and accurately detects the types and positions of fruits and vegetables by using a YOLOv5 algorithm; the control module coordinates the mechanical arm to execute the picking action according to the recognition result, and plans the moving path of the robot to adapt to the complex farmland environment; and the mechanical arm module adopts a multi-degree-of-freedom design and is provided with a flexible clamping jaw, so that efficient picking operation can be completed on the premise of protecting fruits and vegetables. In addition, the system also supports the dynamic updating of the model, and the recognition performance is continuously optimized by adding new fruit and vegetable data. The system can meet the requirements of different crops and environments while improving the picking efficiency and reducing the labor cost, and has wide application prospects.

The invention discloses an orchard dense map construction method and system based on an adaptive ORB threshold and point-line fusion, and the method comprises the steps: employing a FAST corner extraction method of an adaptive threshold in a tracking thread of ORB-SLAM3, solving a corresponding threshold according to the average pixel of a current image under different illumination, carrying out the ORB feature extraction of an image, and carrying out the point-line fusion. The number of feature points extracted under different conditions is increased, and the robustness of the algorithm is improved; aiming at obvious line features of branches and branches in the mulberry field environment, adding a line feature extraction method in a tracking thread at the same time, performing point-line fusion feature tracking, and performing BA optimization on key frame map points generated by the tracking thread to complete local map construction; the method comprises the steps of obtaining a key frame and depth information, performing depth optimization on the obtained key frame and depth information to obtain a camera pose, performing local point cloud construction and splicing according to the camera pose, finally performing global BA optimization on an obtained point cloud map, and constructing an orchard three-dimensional dense map to solve the problem of sparse point cloud information of an original algorithm.

A factory shiitake mushroom picking robot, comprising a moving platform, a base (100), a lifting / lowering device (200), a mushroom stick gripping device (300) and a shiitake mushroom picking device (400), wherein the base (100) is connected to the moving platform, the lifting / lowering device (200) is connected to the base, the mushroom stick gripping device (300) is connected to the lifting / lowering device (200), and the shiitake mushroom picking device (400) is connected to the base (100). The mushroom stick gripping device (300) is used for removing mushroom sticks from a mushroom rack (4). Mushroom stick gripping across different layers is achieved by means of the lifting / lowering device (200). The shiitake mushroom picking device (400) comprises a robotic arm (402) and an end effector (403). Image data of the mushroom sticks is collected by three depth cameras, shiitake mushrooms to be picked are identified by means of multi-view target matching, and quality grade classification is carried out, to achieve graded picking. Also disclosed are a vision-based graded picking method, a shiitake mushroom detection and grading method based on multi-view fusion, and a storage medium for executing the steps of the corresponding methods. The technical problems of existing automated shiitake mushroom picking robots, including low picking efficiency, low degree of automation, susceptibility to damaging mushroom caps and mushroom sticks, and the inability to accurately identify mature shiitake mushrooms are solved.

A crop bale wrap delivery system and method selectively pays out a sheet of wrap at a selectable sheet feed rate selected from a range of sheet feed rates. The wrap delivery system and method selectively pays out a first portion of the wrap onto a rotating crop module at a first sheet feed rate and pays out a second portion of the wrap onto the module at a second sheet feed rate different from the first sheet feed rate. Three or more portions of the wrap may be payed out onto the crop module at three of more differed sheet feed rates that may be selectable by an operator or based on properties of the wrap material or the crop. The wrap feed rate may be a selectable variable or a continuously variable sheet feed rate selected from a range of pay out feeds or feed rates.

The invention discloses a method, a system and equipment for evaluating the grabbing effect of a camellia oleifera picking mechanical arm, and relates to the technical field of stable grabbing of picking robots. The method includes the following steps that physical parameters of a mechanical arm structure and characteristic parameters in the previous picking process are obtained, and the actual grabbing force is calculated according to the parameters. And constructing a finite element analysis model, and performing calibration based on the data to obtain a relative slippage distance predicted value and an actual grasping force predicted value under the current working condition. Then, a relational expression of the branch deflection, the physiological parameters and the actual grasping force is established, fitting parameters are fitted through a least square method, and the branch deflection under the current working condition is calculated. Setting a branch deflection threshold value range, collecting environment temperature, dynamically adjusting an adaptive deflection threshold value, and performing effect evaluation according to a comparison result of the actual grasping force and the deflection threshold value range. According to the method, the fruit picking efficiency is ensured on the premise that the camellia oleifera trees are not damaged.

The invention discloses a double-arm citrus picking robot and a picking method, and belongs to the technical field of agricultural automation equipment. The robot comprises a crawler-type moving chassis, a symmetrically-arranged double-mechanical-arm system, a machine vision system, a citrus collecting bin and a control system. The double-mechanical-arm system adopts a main and auxiliary collaborative framework, the tail end of a main mechanical arm is integrated with a clamping jaw and vacuum suction disc parallel mechanism, an auxiliary mechanical arm is provided with a rotary circular saw blade, and lossless clamping of fruits and precise cutting of fruit stems are achieved. The machine vision system realizes high-precision citrus identification under complex illumination by improving a YOLOv5 network and fusing an HSV dynamic threshold value and Focal Loss optimization; graded path planning is combined with an A * algorithm and an RRT * algorithm, and motion safety of the mechanical arm is ensured through bounding box collision detection. The picking method comprises the steps of three-dimensional semantic map construction, collaborative grabbing and cutting, lossless transfer and the like. The problems that a single-arm robot is low in efficiency, fruits are prone to being damaged, fruit stems are not thoroughly treated and the like are solved, and the robot is suitable for automatic orchard harvesting in hilly areas.

According to the forest and fruit tree body profiling flapping fruit harvester based on the special-shaped crankshaft structure, transmission is achieved through special-shaped crankshafts with different crank throw eccentricity degrees, and the movement amplitude of flapping strips is limited through the inner side edges of amplitude limiting plates; the purpose that the flapping strips are arranged in a manner of imitating the contour of a tree crown can be achieved while the flapping strips are flapped, the flapping strips are arranged in a shape of imitating a tree shape, missed flapping of the top of the tree crown and the pole position of the symmetry axis is avoided, and the net picking rate of different positions is increased. The device comprises a chassis vehicle body and a tree-like flapping device, in the tree-like flapping device, a crankshaft with a plurality of crank throws is rotationally arranged on a base, and the eccentric distances of the crank throws are different; the lower end of each beating strip is hinged to a crank throw of the crankshaft; opposite amplitude limiting plates are arranged on the higher parts of the two sides of the base, and an amplitude limiting hole is formed between the opposite inner side edges of the two amplitude limiting plates; the distance between the inner side edges of the two amplitude limiting plates close to the center of the amplitude limiting plate in the direction parallel to the axial direction of the crankshaft is smaller than the distance between the inner side edges of the two amplitude limiting plates close to the two ends of the amplitude limiting plate.

The invention belongs to the technical field of agricultural picking robot control, and provides an apple picking robot control method based on multi-sensor fusion, which comprises the following steps: deploying an RGB-D camera, a laser radar and a touch sensor, cooperatively collecting data and issuing the data to a system bus, and carrying out timestamp alignment, denoising processing and fusion; the method comprises the following steps: registering collected data to a unified robot coordinate system; establishing a voxel grid to set a voxel state; mapping to form a three-dimensional occupied grid model; obtaining a visibility index according to an RGB-D segmented region; performing weighted fusion in combination with the 3D point cloud set to obtain a fruit position; the method comprises the following steps: generating a motion feasible region by utilizing a three-dimensional occupied grid model, generating candidate poses by fitting a spherical angle increment, traversing the poses to carry out collision judgment, solving a joint track, calculating a quality index and a corresponding fusion weight through real-time sensing data, and carrying out weight adjustment and parameter correction according to a corresponding problem.

A berry harvesting berries system including a mobile platform and a tendon-driven gripper having fingers made of a compliant material, which prevents unwanted damage to the berries.

The utility model discloses an oil palm fruit picking cutter, an oil palm fruit picking device and an oil palm fruit picking equipment, the oil palm fruit picking cutter utilizes a shearing assembly and a self-adaptive clamping assembly to adapt to oil palm fruits of different sizes, the self-adaptive clamping device avoids hooking when leaves are sheared, and the oil palm fruit picking cutter is suitable for the oil palm fruits of different sizes. The self-adaptive clamping device grabs the fruit while the blade cuts off the fruit stem of the fruit, so that the fruit loss caused by falling to the ground is reduced; according to the oil palm fruit picking device, fruits can be accurately and effectively positioned through the tool bit adjusting device, and an operator can pick the fruits at any position with the best visual field; according to the oil palm fruit picking equipment, by additionally arranging the arm frame device and the lifting dumper hopper, when the oil palm fruit picking equipment is used for picking oil palm fruits, large-space-range adjustment can be achieved according to the positions of the oil palm fruits, wireless remote control picking operation can be achieved, meanwhile, after the oil palm fruits are picked, the fruits are directly collected into the dumper hopper of the oil palm fruit picking equipment, and then transferring operation is completed; picking procedures are simplified, and labor intensity is reduced.